Network Meta-Analysis of Pharmacological Therapies for Long-Term Prophylactic Treatment of Patients with Hereditary Angioedema
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Several treatments for long-term prophylaxis (LTP) of hereditary angioedema (HAE) are in clinical use, such as garadacimab, lanadelumab, subcutaneous C1 esterase inhibitor (C1INH), and berotralstat. In the absence of head-to-head comparative evidence, indirect comparison methods are needed to compare LTP treatments in patients with HAE. The objective of this analysis was to estimate the comparative efficacy, safety, and impact on quality of life of LTP treatments for patients with HAE through NMAs. METHODS: A systematic literature review was conducted to identify randomized controlled trials (RCTs) investigating LTP treatments in patients (at least 12 years old) with HAE (PROSPERO protocol #CRD42022359207). A network meta-analysis (NMA) feasibility assessment evaluated trial suitability and Bayesian NMAs were conducted for evaluable efficacy, safety, and quality of life (QoL) outcomes. RESULTS: The results of these NMAs show improved efficacy, QoL, and reduced rate of adverse events with garadacimab (200 mg once monthly), lanadelumab (300 mg every two or four weeks), subcutaneous C1INH (60 IU/kg twice weekly), and berotralstat (150 mg once daily) compared to placebo in the treatment of patients with HAE. For the primary outcome of time-normalized number of HAE attacks, garadacimab statistically significantly reduced the rate of attacks compared to lanadelumab Q4W and berotralstat. A similar statistically significant reduction was shown for HAE attacks treated with on-demand treatment. Garadacimab showed statistically significant reduction in the rate of moderate and/or severe HAE attacks compared to lanadelumab Q2W. Garadacimab also showed statistical improvements in change from baseline in AE-QoL total score as compared to berotralstat. CONCLUSIONS: Overall, garadacimab ranked as the most probable effective treatment among all comparators assessed, with lanadelumab Q2W or subcutaneous C1INH ranking second, across most outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.050 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".